Instructions to use Mattimax/DACMini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mattimax/DACMini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Mattimax/DACMini")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Mattimax/DACMini") model = AutoModelForCausalLM.from_pretrained("Mattimax/DACMini") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Mattimax/DACMini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Mattimax/DACMini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mattimax/DACMini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Mattimax/DACMini
- SGLang
How to use Mattimax/DACMini with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Mattimax/DACMini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mattimax/DACMini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Mattimax/DACMini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mattimax/DACMini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Mattimax/DACMini with Docker Model Runner:
docker model run hf.co/Mattimax/DACMini
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* Dataset: [italian-dataset-mini](https://huggingface.co/datasets/ruslanmv/italian-dataset-mini)
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* Autore: [Mattimax](https://huggingface.co/Mattimax)
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* Organizzazione: [M.INC](https://huggingface.co/MINC01)
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* Collezione: [Little_DAC Collection](https://huggingface.co/collections/Mattimax/little-dac-collection-68e11d19a5949d08e672b312)
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* Dataset: [italian-dataset-mini](https://huggingface.co/datasets/ruslanmv/italian-dataset-mini)
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* Autore: [Mattimax](https://huggingface.co/Mattimax)
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* Organizzazione: [M.INC](https://huggingface.co/MINC01)
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* Collezione: [Little_DAC Collection](https://huggingface.co/collections/Mattimax/little-dac-collection-68e11d19a5949d08e672b312)
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## Citazione
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Se utilizzi **Mattimax/DACMini** in un progetto, un articolo o qualsiasi lavoro, ti chiediamo gentilmente di citarlo usando il file `CITATION.bib` incluso nel repository:
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```bibtex
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@misc{mattimax2025dacmini,
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title = {{Mattimax/DACMini}: Un modello di linguaggio open source},
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author = {Mattimax},
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howpublished = {\url{https://huggingface.co/Mattimax/DACMini}},
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year = {2025},
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note = {License: MIT. Se usi questo modello, per favore citane la fonte originale.}
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}
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```
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